Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising the acts: with a camera-equipped robot system at a first position in an aisle of a retail store, capturing first imagery from a shelving unit to one side of said aisle, the first imagery depicting a first visual beacon; and after moving a distance down the store aisle, the robot system capturing second imagery from said shelving unit, the second imagery depicting a second, different, visual beacon; wherein the first and second visual beacons are both formed by printing at different locations along a single elongated printed shelf label; wherein the first visual beacon is positioned proximate to a first item on a shelf of said shelving unit, said first visual beacon comprising a first machine readable indicia useful to identify the first item, and the second visual beacon is positioned proximate to a second item on said shelf, the second visual beacon comprising a second machine readable indicia useful to identify the second item, wherein the visual beacons serve as navigational landmarks while also enabling identification of proximate items stocked in the shelving unit; and wherein the relative position of the first visual beacon to the second visual beacon cannot become mis-adjusted because the relative position is fixed by printing of said beacons on a common substrate, thereby helping assure accuracy of the robot system operation.
A robot system equipped with a camera navigates through a retail store aisle, capturing imagery from shelving units on either side. The system first captures imagery at a starting position, detecting a first visual beacon printed on an elongated shelf label. This beacon is positioned near a first item on the shelf and includes machine-readable indicia for identifying the item. After moving down the aisle, the system captures additional imagery, detecting a second, distinct visual beacon printed on the same shelf label near a second item. This beacon also contains machine-readable indicia for identifying its proximate item. The beacons serve dual purposes: they act as navigational landmarks for the robot while also enabling item identification. Since both beacons are printed on a single, continuous label, their relative positions remain fixed, ensuring accurate navigation and item recognition. This design prevents misalignment issues that could arise if the beacons were separate, thereby improving the reliability of the robot's operations in tracking inventory and navigating store aisles.
2. The method of claim 1 in which said distance is more than two feet, and said printed shelf label is more than two feet in length.
This invention relates to a system for printing and applying shelf labels in retail or warehouse environments. The problem addressed is the difficulty of accurately printing and positioning long shelf labels, particularly those exceeding two feet in length, to ensure proper alignment and readability. Traditional methods often result in misalignment, wrinkling, or improper adhesion, leading to inefficiencies in inventory management and customer experience. The invention describes a method for printing and applying a shelf label that is more than two feet in length. The system includes a printing mechanism capable of producing labels of this extended length and an application mechanism designed to securely affix the label to a shelf or surface. The printing mechanism ensures high-quality printing across the entire length of the label, while the application mechanism accounts for the label's size to prevent misalignment or damage during placement. The system may also include sensors or alignment tools to verify proper positioning before final attachment. The method involves printing the label to the required length, transporting it to the application mechanism, and then applying it to the shelf with precision. The system is particularly useful in large retail or warehouse settings where long labels are needed for bulk items or wide shelving. The invention improves efficiency by reducing manual labor and ensuring consistent, accurate label placement.
3. The method of claim 1 in which said first and second visual beacons comprise identifiers that are steganographically encoded on said shelf label, so that they are not apparent to shoppers in said store aisle.
This invention relates to a system for tracking and managing retail inventory using visual beacons embedded in shelf labels. The problem addressed is the need for discreet, shopper-unnoticeable identifiers that can be detected by automated systems to monitor product placement, stock levels, and pricing accuracy without disrupting the shopping experience. The system uses shelf labels with steganographically encoded visual beacons. These beacons contain identifiers that are imperceptible to shoppers but can be detected by cameras or sensors in the store aisle. The identifiers are embedded in the label design using techniques like micro-patterns, color variations, or subtle distortions that are only recognizable by image processing algorithms. This allows the system to track product locations, verify correct pricing, and detect out-of-stock items without requiring visible barcodes or QR codes. The method involves capturing images of the shelf labels using in-store cameras, processing the images to extract the steganographic identifiers, and comparing the detected identifiers against a product database to confirm the correct items are displayed. The system can also detect misplaced or missing labels, ensuring accurate inventory management. The steganographic encoding ensures the identifiers remain hidden from shoppers, maintaining a clean and uncluttered retail environment while enabling automated monitoring.
4. The method of claim 3 that further includes decoding one of said steganographically-encoded identifiers, and accessing a first data structure to determine a physical location in the store aisle corresponding thereto.
This invention relates to a system for guiding customers within a retail store using steganographically-encoded identifiers. The problem addressed is the difficulty customers face in locating products within large or complex store layouts, often leading to frustration and lost sales opportunities. The solution involves embedding steganographic identifiers in visual elements of the store, such as signage, product packaging, or digital displays. These identifiers are imperceptible to the human eye but can be detected by a customer's mobile device or other scanning device. The method includes capturing an image or video of the steganographically-encoded identifier, decoding the identifier to extract location information, and accessing a data structure that maps the identifier to a specific physical location within a store aisle. The system then provides navigation instructions to guide the customer to the desired product. The data structure may also include additional information, such as product details, promotions, or inventory status, to enhance the shopping experience. This approach improves customer navigation efficiency while maintaining a visually uncluttered store environment.
5. The method of claim 4 that further includes accessing a second data structure to determine which item should be shelved proximate to the visual beacon from which the identifier was decoded.
This invention relates to automated shelving systems that use visual beacons to guide the placement of items in a storage environment. The problem addressed is the efficient and accurate shelving of items in a way that optimizes space utilization and retrieval efficiency. The system employs visual beacons, such as QR codes or barcodes, to identify specific shelving locations. When an item is to be shelved, a visual beacon is scanned to decode an identifier associated with that location. The system then accesses a second data structure to determine which item should be placed near the scanned beacon. This data structure contains shelving rules or proximity guidelines, ensuring that related or frequently accessed items are grouped together. The method may also involve verifying the correct placement of the item by cross-referencing the decoded identifier with the item's attributes, such as size, category, or expiration date. The system may further adjust shelving recommendations dynamically based on real-time inventory data or user preferences. The overall goal is to improve inventory management by reducing search time and minimizing errors in item placement.
6. The method of claim 5 in which the first and second data structures comprise a common data structure.
Technical Summary: This invention relates to data processing systems, specifically methods for managing and organizing data structures to improve efficiency and reduce redundancy. The problem addressed is the inefficiency and complexity that arises when multiple data structures are used to store related information, leading to increased memory usage, processing overhead, and potential inconsistencies. The solution involves using a single, unified data structure to replace multiple separate data structures. This common data structure consolidates the data that would otherwise be distributed across different structures, eliminating redundancy and simplifying data management. By integrating the data into one structure, the system reduces the need for multiple lookups, updates, and synchronization operations, thereby improving performance and reducing the risk of errors. The common data structure is designed to handle the functions previously performed by the separate data structures, ensuring that all necessary data is accessible in a single location. This approach is particularly useful in applications where data is frequently accessed, modified, or shared between different system components. The unified structure allows for faster data retrieval and updates, as well as easier maintenance and scalability. Overall, the invention provides a more efficient and streamlined way to manage data, reducing complexity and improving system performance by consolidating multiple data structures into one.
7. The method of claim 1 in which said first and second visual beacons comprise identifiers that are steganographically encoded on said shelf label, so that they are not apparent to shoppers in said store aisle, the shelf label also including lettering printed thereon that conveys product information to said shoppers, but said shelf label lacking any visible barcode marking.
This invention relates to a retail shelf labeling system that uses steganographically encoded visual beacons to facilitate product identification and inventory management while maintaining a clean, uncluttered appearance for shoppers. The system addresses the problem of traditional barcode labels, which can be visually distracting and may not integrate seamlessly with store aesthetics. Instead, the shelf labels incorporate hidden visual beacons that are imperceptible to shoppers but can be detected by automated systems, such as cameras or scanners, to identify products. These beacons are steganographically encoded, meaning they are embedded in the label's design or lettering in a way that does not disrupt the visual presentation of product information. The labels also include standard lettering to convey product details to customers, but they intentionally exclude visible barcode markings. This approach allows for automated tracking and inventory management without compromising the visual appeal of the retail environment. The system ensures that product identification remains efficient for store operations while maintaining a shopper-friendly display. The hidden beacons enable seamless integration with automated checkout or inventory systems, reducing the need for manual scanning while preserving the aesthetic integrity of the shelf labels.
8. The method of claim 1 in which said distance is more than four feet, and said printed shelf label is more than four feet in length.
A system and method for printing and applying large-format shelf labels in retail or warehouse environments addresses the challenge of efficiently labeling long shelves or storage areas where standard-sized labels are impractical. The invention involves a printing mechanism capable of producing labels exceeding four feet in length, ensuring full coverage of extended shelving units. The system includes a positioning mechanism that ensures precise alignment of the label along the shelf, maintaining readability and consistency. The method further incorporates a distance measurement component to verify that the label spans the required length, typically more than four feet, to cover the entire shelf surface. This ensures accurate product identification and inventory management in large-scale storage or retail settings. The invention improves operational efficiency by reducing the need for multiple smaller labels and minimizing labeling errors, particularly in environments where long shelves are common. The system may also include automated or semi-automated application mechanisms to streamline the labeling process, reducing labor time and enhancing accuracy. The solution is particularly useful in warehouses, supermarkets, or other facilities where large shelving units require consistent and durable labeling.
9. The method of claim 1 in which the first and second items also bear machine-readable identification information, and the method includes detecting said machine-readable identification information from the first and second items, and checking that the first and second items are properly positioned on the shelf by determining position of the first item relative to the first visual beacon, and determining position of the second item relative to the second visual beacon.
This invention relates to a system for monitoring and verifying the placement of items on a shelf using visual beacons and machine-readable identification. The problem addressed is ensuring items are correctly positioned on shelves, which is critical for inventory management, automated retail systems, and visual merchandising. The system uses visual beacons, such as markers or patterns, placed on the shelf to define specific locations for items. Each item also bears machine-readable identification, such as barcodes, QR codes, or RFID tags, which are detected by a scanning device. The system determines the position of each item relative to its assigned visual beacon to verify proper placement. By comparing the detected positions of the items to their expected positions, the system can confirm whether the items are correctly positioned or identify misplacements. This method enhances accuracy in inventory tracking, reduces manual verification efforts, and improves the efficiency of automated retail and logistics operations. The system may be integrated with robotic systems or handheld scanners for real-time monitoring and correction of item placement.
10. The method of claim 1 that includes activating a light source with a first spectrum to illuminate a shelf when the robot is at a first location, wherein said first location is determined by reference to the first visual beacon.
This invention relates to robotic systems for shelf inventory management, specifically addressing challenges in accurately locating and identifying shelves in retail or warehouse environments. The system uses visual beacons to determine the robot's position relative to shelves, enabling precise navigation and inventory tracking. A key feature is the activation of a light source with a specific spectrum to illuminate the shelf when the robot reaches a predefined location, as determined by the first visual beacon. This illumination enhances the robot's ability to capture high-quality images or sensor data of the shelf contents, improving inventory accuracy. The light source's spectrum is selected to optimize visibility of shelf items under varying lighting conditions, ensuring consistent performance. The system may also include additional visual beacons to guide the robot along predefined paths or to multiple shelves, ensuring comprehensive coverage of the inventory area. The combination of positional tracking via beacons and controlled illumination creates a robust solution for automated shelf monitoring, reducing human labor and improving inventory management efficiency.
11. The method of claim 10 that further includes activating a light source with a second spectrum, different than the first spectrum, to illuminate a shelf when the robot is at a second location, different than the first location, wherein said second location is determined by reference to the second visual beacon.
This invention relates to robotic systems for navigating and interacting with retail environments, particularly focusing on shelf monitoring and inventory management. The problem addressed is the need for robots to accurately locate themselves within a store and perform tasks such as scanning shelves for stock levels or product placement, often under varying lighting conditions. The method involves a robot equipped with sensors and a light source that emits a first spectrum of light to illuminate a shelf at a first location. The robot identifies this location using a first visual beacon, which may be a marker or pattern placed in the environment. To enhance visibility or adjust for different tasks, the robot can activate a second light source with a different spectrum (e.g., switching from white to infrared) when it reaches a second location, determined by a second visual beacon. This allows the robot to adapt its illumination based on position, improving image capture quality for tasks like barcode scanning or product recognition. The system ensures precise navigation and task execution by dynamically adjusting lighting parameters in response to the robot's position relative to predefined beacons.
12. The method of claim 1 that further includes: determining, using the data conveyed by the first machine readable indicia, that the first item should be marked with steganographically-encoded machine-readable data; applying a detector to sense steganographically-encoded data from the first item; and issuing an alert to store personnel if said detector does not sense steganographically-encoded data from the first item; wherein failure to sense steganographically-encoded data from the first item can indicate that the first item is counterfeit.
This invention relates to anti-counterfeiting systems that use steganographic encoding to verify the authenticity of items. The system addresses the problem of counterfeit goods by embedding machine-readable data invisibly into items, allowing for detection of unauthorized reproductions. The method involves scanning an item to determine whether it should be marked with steganographically-encoded data. If the item is identified as requiring such marking, a detector is applied to check for the presence of the encoded data. If no steganographic data is detected, an alert is issued to store personnel, indicating a potential counterfeit item. The system leverages steganography to embed data imperceptibly, making it difficult for counterfeiters to replicate without detection. The detection process ensures that only items with the correct encoded data are deemed authentic, enhancing supply chain security. The method can be applied to various items, including packaging, labels, or products, to prevent counterfeit distribution. The use of steganography provides a tamper-resistant verification mechanism, reducing the risk of fraudulent items entering the market.
13. The method of claim 1 in which the first and second machine readable indicia are among plural indicia printed edge-to-edge along said elongated shelf label.
This method details an automated store shelf inspection process using a camera-equipped robot system. At a starting point in a store aisle, the robot captures initial images of a shelving unit, detecting a first visual beacon. After moving a distance, the robot captures further images of the same unit, detecting a second, different visual beacon. Both beacons are printed at distinct locations on a single, elongated shelf label. The first beacon, positioned near a first product, includes machine-readable data to identify that product, and the second beacon, near a second product, includes machine-readable data for it. These visual beacons function as navigational landmarks for the robot and enable identification of nearby products. Crucially, their relative positions are fixed by their common printing on the label, ensuring accuracy. Furthermore, the first and second machine-readable data are among multiple such data segments printed continuously, edge-to-edge, along the entire length of the elongated shelf label. ERROR (embedding): Error: Failed to save embedding: Could not find the 'embedding' column of 'patent_claims' in the schema cache
14. The method of claim 1 in which the first and second machine readable indicia are among plural indicia printed along said elongated shelf label, with gaps between successive ones of the plural indicia.
This invention relates to a system for printing and applying machine-readable indicia, such as barcodes or QR codes, along elongated shelf labels used in retail or inventory management. The problem addressed is the need for efficient, accurate, and space-optimized placement of multiple machine-readable codes on a single label while ensuring readability and minimizing errors during scanning. The method involves printing a series of machine-readable indicia along the length of an elongated shelf label, with defined gaps between successive indicia. Each indicia is uniquely associated with a product or item, allowing for quick identification and inventory tracking. The gaps between indicia ensure that each code can be individually scanned without interference from adjacent codes, improving accuracy. The system may also include alignment features to ensure proper positioning of the label on shelves, further enhancing scanning reliability. The indicia can be printed in a linear or staggered arrangement, depending on the label length and the number of items to be identified. The method may also include error-checking mechanisms to verify the integrity of the printed codes before application. This approach improves inventory management by reducing manual scanning errors and streamlining the process of updating product information. The system is particularly useful in retail environments where multiple products are displayed on a single shelf, requiring efficient and accurate labeling.
15. The method of claim 1 in which the first visual beacon comprises plural square blocks printed at successive positions along said elongated shelf label.
A system and method for visual beacon-based product identification in retail environments addresses the challenge of accurately and efficiently locating products on shelves using mobile devices. Traditional barcode scanning requires close proximity and precise alignment, while image recognition systems often struggle with cluttered or poorly lit shelves. The invention employs visual beacons—distinctive, machine-readable patterns printed on elongated shelf labels—to enable rapid and reliable product identification. These beacons are detected by a mobile device's camera, allowing the device to determine the product's location and retrieve associated information, such as pricing or inventory status, without requiring direct scanning. The visual beacon comprises multiple square blocks arranged at successive positions along the shelf label. These blocks form a pattern that encodes data, such as product identifiers or shelf coordinates, which can be decoded by the mobile device. The use of square blocks ensures robustness against partial occlusion or low-resolution imaging, while their sequential arrangement along the label allows for flexible placement and easy alignment with the product. The system may also include additional visual beacons or reference markers to enhance accuracy, particularly in environments with multiple shelves or overlapping labels. By leveraging these beacons, the method enables seamless integration with existing retail infrastructure, improving the efficiency of product lookup and inventory management.
16. The method of claim 1 in which the first and second items also bear machine-readable identification information, and the method includes: determining a first computational budget for decoding machine-readable identification information from the first item, by reference to the first visual beacon; determining a second computational budget for decoding machine-readable identification information from the second item, by reference to the second visual beacon; and decoding machine-readable identification information from the first and second items, including applying said determined first and second computational budgets, respectively.
This invention relates to a method for decoding machine-readable identification information from physical items using visual beacons. The problem addressed is efficiently allocating computational resources when decoding identification information from multiple items in a shared environment, where visual beacons are used to locate and process the items. The method involves first and second physical items, each bearing machine-readable identification information and associated with respective visual beacons. The visual beacons provide spatial or contextual cues to locate the items. The method determines a first computational budget for decoding the identification information from the first item by analyzing the first visual beacon, and similarly determines a second computational budget for the second item by analyzing the second visual beacon. The computational budgets allocate processing resources, such as CPU time or memory, based on factors like beacon visibility, item proximity, or decoding complexity. The method then decodes the identification information from both items, applying the respective computational budgets to optimize resource usage while ensuring accurate decoding. This approach improves efficiency in environments where multiple items must be processed simultaneously, such as inventory management or automated sorting systems.
17. The method of claim 1 in which the first and second items also bear machine-readable identification information, and the method includes assessing a position of the first item on the shelf, and controlling illumination cast onto the first item by a light source on the robot, in accordance with said position.
This invention relates to automated inventory management systems using robotic devices equipped with illumination control. The system addresses challenges in accurately tracking and identifying items on shelves, particularly in environments where lighting conditions may vary or where items are partially obscured. The method involves a robot equipped with a light source that dynamically adjusts illumination based on the position of an item to enhance visibility and readability of machine-readable identification information, such as barcodes or QR codes, on the item. The robot assesses the position of the item on the shelf, then controls the light source to optimize illumination for capturing clear images or scans of the identification information. This ensures reliable identification and tracking of items, even in suboptimal lighting conditions. The system may also include additional features such as robotic movement to align the light source with the item, image processing to verify identification, and data transmission to update inventory records. The invention improves efficiency in inventory management by reducing errors in item identification and tracking.
18. The method of claim 17 in which assessing the position of the first item on the shelf comprises assessing a scale of the machine-readable identification information on the first item.
This invention relates to automated systems for monitoring and managing inventory on retail shelves. The problem addressed is the difficulty in accurately tracking the position and availability of items on shelves, which can lead to stockouts, misplaced products, or inefficient restocking. The solution involves using machine-readable identification information, such as barcodes or QR codes, to determine the precise location of items on shelves. The method includes capturing an image of a shelf containing multiple items, where at least one item has machine-readable identification information. The system processes the image to detect and decode this information, then assesses the position of the item by analyzing the scale of the identification information in the image. The scale refers to the size or resolution of the identification information, which can indicate the item's distance from the imaging device or its placement on the shelf. This assessment helps determine whether the item is correctly positioned, missing, or misplaced. The method may also involve comparing the detected position with a predefined shelf layout to identify discrepancies. If an item is found to be out of place or missing, the system can generate alerts for restocking or repositioning. The approach improves inventory accuracy, reduces manual labor, and enhances customer satisfaction by ensuring products are readily available. The system can be integrated into retail environments, warehouses, or automated stores to streamline inventory management.
19. The method of claim 17 in which assessing the position of the first item on the shelf comprises imaging with a depth sensing camera.
A system and method for monitoring and managing inventory in a retail or storage environment involves tracking the position and orientation of items on shelves using depth sensing cameras. The technology addresses challenges in automated inventory management, such as accurately detecting item placement, orientation, and potential misplacement, which can lead to stockouts or inefficiencies in restocking processes. The method includes capturing depth data of a shelf using a depth sensing camera, which provides three-dimensional information about the items' positions and orientations. This data is processed to assess whether items are correctly placed, properly oriented, and aligned with predefined shelf layouts. The system may also compare the captured data against a reference model or database to identify discrepancies, such as missing items, incorrect orientations, or misplaced products. The depth sensing camera enables precise spatial measurements, improving accuracy over traditional 2D imaging methods. The system can generate alerts or instructions for restocking or repositioning items, enhancing inventory accuracy and operational efficiency. The method may be integrated into automated retail systems, warehouses, or smart shelves to streamline inventory management and reduce manual labor.
Unknown
February 4, 2020
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